Some Remarks on the Method of Fundamental Solutions for Two- Dimensional Elasticity

In this paper,some remarks for more efficient analysis of two-dimensional elastostatic problems using the method of fundamental solutions are made.First,the effects of the distance between pseudo and main boundaries on the solution are investigated and by a numerical study a lower bound for the distance of each source point to the main boundary is suggested.In some cases,the resulting system of equations becomes ill-conditioned for which,the truncated singular value decomposition with a criterion based on the accuracy of the imposition of boundary conditions is used.Moreover,a procedure for normalizing the shear modulus is presented that significantly reduces the condition number of the system of equations.By solving two example problems with stress concentration,the effectiveness of the proposed methods is demonstrated.

Two-dimensional Parameter Relationships for W UMa-type Systems Revisited

Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary systems.In this investigation,two-dimensional(2D)relationships for P–MV(system),P–L1,2,M1,2–L1,2,and q–Lratiowere revisited.The sample used is related to 118 contact binary systems with an orbital period shorter than 0.6 days whose absolute parameters were estimated based on the Gaia Data Release 3 parallax.We reviewed previous studies on 2D relationships and updated six parameter relationships.Therefore,Markov chain Monte Carlo and Machine Learning methods were used,and the outcomes were compared.We selected 22 contact binary systems from eight previous studies for comparison,which had light curve solutions using spectroscopic data.The results show that the systems are in good agreement with the results of this study.

A method of measuring the [α/Fe] ratios from the spectra of the LAMOST survey

The [α/Fe] ratios in stars are good tracers to probe the formation history of stellar populations and the chemical evolution of the Galaxy. The spectroscopic survey of LAMOST provides a good opportunity to determine [α/Fe] of millions of stars in the Galaxy. We present a method of measuring the [α/Fe]ratios from LAMOST spectra using the template-matching technique of the LSP3 pipeline. We use three test samples of stars selected from the ELODIE and MILES libraries, as well as the LEGUE survey to validate our method. Based on the test results, we conclude that our method is valid for measuring [α/Fe]from low-resolution spectra acquired by the LAMOST survey. Within the range of the stellar parameters Teff= [5000, 7500] K, log g = [1.0, 5.0] dex and [Fe/H]= [onsistent with values derived from high-resolution spectra,-1.5, ＋0.5] dex, our [α/Fe] measurements are c and the accuracy of our [α/Fe] measurements from LAMOST spectra is better than 0.1 dex with spectral signal-to-noise higher than 20.

A star-based method for precise wavelength calibration of the Chinese Space Station Telescope(CSST) slitless spectroscopic survey

The Chinese Space Station Telescope(CSST)spectroscopic survey aims to deliver high-quality low-resolution(R>200)slitless spectra for hundreds of millions of targets down to a limiting magnitude of about 21 mag,distributed within a large survey area(17500 deg2)and covering a wide wavelength range(255-1000 nm by three bands GU,GV,and GI).As slitless spectroscopy precludes the usage of wavelength calibration lamps,wavelength calibration is one of the most challenging issues in the reduction of slitless spectra,yet it plays a key role in measuring precise radial velocities of stars and redshifts of galaxies.In this work,we propose a star-based method that can monitor and correct for possible errors in the CSST wavelength calibration using normal scientific observations,taking advantage of the facts that(ⅰ)there are about ten million stars with reliable radial velocities now available thanks to spectroscopic surveys like LAMOST,(ⅱ)the large field of view of CSST enables efficient observations of such stars in a short period of time,and(ⅲ)radial velocities of such stars can be reliably measured using only a narrow segment of CSST spectra.We demonstrate that it is possible to achieve a wavelength calibration precision of a few km s^(-1) for the GU band,and about 10 to 20 kms^(-1) for the GV and GI bands,with only a few hundred velocity standard stars.Implementations of the method to other surveys are also discussed.

Stellar spectra association rule mining method based on the weighted frequent pattern tree

Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.

The W UMa binaries USNO-A2.0 1350-17365531,V471 Cas,V479 Lac and V560 Lac:light curve solutions and global parameters based on Gaia distances

We present photometric observations in Sloan filters g′, i′of the eclipsing W UMa stars USNOA2.0 1350-17365531, V471 Cas, V479 Lac and V560 Lac. The sinusoidal-like O-C diagram of V471 Cas indicates the presence of a third body with mass 0.12 M_⊙(a red dwarf) at distance 897 R_⊙. The O-C diagram of V479 Lac reveals a period decrease of d P/dt =-1.69 × 10-6d yr-1. The results of the light curve solutions are:(i) the targets are overcontact binaries with small fill-out factors;(ii) their components are F–K stars, comparable in size, whose temperature differences are below 80 K;(iii) all targets undergo partial eclipses and to limit the possible mass ratios we carried out two-step q-search analysis. The target global parameters(luminosities, radii, masses) were obtained on the basis of their Gaia distances and the results of our light curve solutions. The obtained total mass of V560 Lac turns out to be smaller than the lower mass limit for presently known W UMa binaries of 1.0-1.2 M_⊙, i.e. this target is a peculiar overcontact system.

Estimating stellar atmospheric parameters based on Lasso features

With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.

Parameterizing Stellar Spectra Using Deep Neural Networks

Large-scale sky surveys are observing massive amounts of stellar spectra. The large number of stellar spectra makes it necessary to automatically parameterize spectral data, which in turn helps in statistically exploring properties related to the atmospheric parameters. This work focuses on designing an automatic scheme to estimate effective temperature （Tee）, surface gravity （log g） and metallicity [Fe/H] from stellar spectra. A scheme based on three deep neural networks （DNNs） is proposed. This scheme consists of the following three procedures： first, the configuration of a DNN is initialized using a series of autoencoder neural networks; second, the DNN is fine-tuned using a gradient descent scheme; third, three atmospheric parameters Tefr, log 9 and [Fe/H] are estimated using the computed DNNs. The constructed DNN is a neural network with six layers （one input layer, one output layer and four hidden layers）, for which the number of nodes in the six layers are 3821, 1000, 500, 100, 30 and 1, respectively. This proposed scheme was tested on both real spectra and theoretical spectra from Kurucz＇s new opacity distribution function models. Test errors are measured with mean absolute errors （MAEs）. The errors on real spectra from the Sloan Digital Sky Survey （SDSS） are 0.1477, 0.0048 and 0.1129 dex for log 9, log Tefr and [Fe/H] （64.85 K for Teff）, respectively. Regarding theoretical spectra from Kurucz＇s new opacity distribution function models, the MAE of the test errors are 0.0182, 0.0011 and 0.0112 dex for log 9, log Teff and [Fe/H] （14.90 K for Tdf）, respectively.

Estimating Photometric Redshifts with Artificial Neural Networks and Multi-Parameters

We calculate photometric redshifts from the Sloan Digital Sky Survey Data Release 2 （SDSS DR2） Galaxy Sample using artificial neural networks （ANNs）. Different input sets based on various parameters （e.g. magnitude, color index, flux information） are explored. Mainly, parameters from broadband photometry are utilized and their performances in redshift prediction are compared. While any parameter may be easily incorporated in the input, our results indicate that using the dereddened magnitudes often produces more accurate photometric redshifts than using the Petrosian magnitudes or model magnitudes as input, but the model magnitudes are superior to the Petrosian magnitudes. Also, better performance resuits when more effective parameters are used in the training set. The method is tested on a sample of 79 346 galaxies from the SDSS DR2. When using 19 parameters based on the dereddened magnitudes, the rms error in redshift estimation is σz = 0.020184. The ANN is highly competitive tool compared to the traditional template-fitting methods when a large and representative training set is available.

用小波分析方法计算BL Lac天体S5 0716+714的光变周期

介绍了一种用小波分析寻找BL Lac天体S5 0716+714光变周期的方法.收集了BL Lac天体S5 0716+714光学B、V、R、I四个波段较完备的观测数据,获得了10天平均的长期光变曲线.使用此光变曲线数据进行小波分析计算,结果表明小波分析方法能较好地分析和认证BL Lac天体的光变周期值.从小波变换系数实部的等值线图,可以准确证认BL Lac天体S5 0716+714有光变周期波动变化.由B,V,R,I四个波段的小波方差曲线分析发现BL Lac天体S5 0176+714有一个1160天的稳定周期,这个结果与Raiteri等人发现的3.3年周期是一致的.预测在2011年8月将有一次大的爆发.

电动汽车驱动用内置式永磁同步电机直交轴电感参数计算与实验研究

准确计算电动汽车驱动用内置式永磁同步电机工作点电感参数Ld、Lq,对电机性能的预判以及高精度控制非常关键。驱动用内置式永磁同步电机转子上无自起动笼型条,有限元带载起动计算困难,本文通过确定带额定负载起动时转子初始位置,实现了30k W样机有限元带额定负载起动以及负载饱和磁场计算,为样机负载工作点电感参数准确求解提供计算基础。在永磁同步电机电感计算理论的基础上,分别采用忽略交叉饱和影响的有限元法以及冻结磁导率法计算了样机电感参数。并对30k W样机电感参数采用静态交流实验法进行了实验测量。通过对比,忽略交叉饱和影响的电感参数计算值与静态实测电感值相吻合,采用冻结磁导率法计算的q轴电感值比静态实测q轴电感值减小了20.5%,冻结磁导率法计算的d轴电感值比静态实测d轴电感值增大了38.1%。说明忽略交叉饱和影响有限元法可以准确计算样机的静态不饱和电感参数,但负载时样机磁路交叉饱和效应严重,此时采用考虑交叉饱和影响的冻结磁导率法计算样机电感参数更为准确。

能量色散X射线荧光分析基本参数法研究

本文介绍了EDXRF中基本参数法原理和计算方法,基于此方法用C语言设计编写了基本参数法的计算程序。通过配制的合金样用该法测定其成分含量,结果表明所测合金样的成分含量与其化学分析结果基本上一致,精确度较高,相对标准偏差不超过1.3%。

光谱预处理及其对星系/类星体分类结果的影响

由于噪声、畸变和观测环境等因素的影响,在天体光谱自动处理之前,需要对它进行相应的预处理.研究巡天光谱的预处理(数据格式和流量标准化)对光谱自动分析的影响.分析了同数据格式对光谱及其谱线特征的影响和格式标准化研究的必要性;通过分析光谱流量数量级的不确定性及其特点,提出了流量数量级变化的基本模型,并给出了相应的标准化方法.通过星系和类星体的分类实验,结果表明:1)采用对数波长数据格式对光谱的自动分类更有利;2)验证了所提出的流量标准化模型的合理性,以及所给流量标准化方法良好的性能.特别需要指出的是,文献中通常采用的流量标准化方法在光谱自动分类中的效果反而是较差的.

用WWZ变换分析类星体3C 345的光变周期

介绍了一种全新的基于小波分析原理的处理非等间隔数据的方法:加权小波Z变换(Weighted Wavelet Z-transform,WWZ).收集了类星体3C 345光学B波段100多年来较为完整的观测数据,获得了其长期光变曲线.利用WWZ变换对3C 345 B波段28 yr的光变数据进行分析,通过研究发现3C 345的光变曲线中包含有624～941 d、4.54～5.23 yr和9.59～11.51 yr的周期成分,并分析了它们随时间演化的情况.其中后两个周期成分属于稳定周期,而前一个周期成分波动比较大,可以推测它并不是一个稳定周期.

X射线荧光基本参数法测定Y_(1-x)Ce_xBa_2Cu_3O_y中的钇铈钡铜

本文用Ｘ射线荧光光谱基本参数法测定了Ｙ１－ｘＣｅｘＢａ２Ｃｕ３Ｏｙ系列样品中的钇铈钡铜含量，然后折算成它们的原子比，测量的结果与ＩＣＰ的结果接近。为非破坏地测定高温超导体的实际组分进行了一次尝试。

X射线荧光光谱分析中基体效应的数学校正方法新探

用开发的ＴＢＨＸＲＦ基本参数法程序计算了复杂样品的基体效应。提出一个修正多元体系基体效应的校正数学模型和计算影响系数α及β，导出的校正模式及影响系数的物理意义清楚、明确。用该法分析了不锈钢样品获得良好的结果。还指出在某些情况中，三次荧光的影响不能忽略，从对比实验中得出结论，对Ｎｉ浓度高的钢铁样品在分析Ｃｒ时，必须考虑Ｎｉ、Ｆｅ对ＣｒＫα的三次荧光效应影响。

质量衰减系数的计算与应用

质量衰砬系数μｍ是Ｘ射线理论强度计算中一项必需而重要的基本参数。它包括元素本身、元素间和元素对某波长的质量吸收。本文选用四种拟合式，用Ｃ语言编制成程序；任选波长计算与实验值进行比较，确定其精确度，提供给ＦＰ法计算初级和次级激发理论强度。

恒星大气物理参量的非参数估计方法

恒星大气物理参量(有效温度、表面重力、化学丰度)是导致恒星光谱差异的 主要因素．恒星大气物理参量的自动测量是LAMOST等大规模巡天望远镜所产生的海量 天体光谱数据自动处理中一个重要研究内容．针对测量大样本的恒星光谱数据估计每个恒 星的大气物理参量,提出了一种基于变窗宽核函数的估计算法:变窗宽算法是对固定窗宽 算法的改进,分为3个步骤: (1)将历史恒星光谱数据进行PCA处理,得到光谱的低 维特征数据;(2)利用特征数据与其物理参数的对应关系,建立一种变窗宽的非参数估计 模型; (3)利用该估计模型,直接计算待测恒星光谱的3个物理参量(有效温度、表面重 力、金属丰度)．实验结果表明:该方法与固定窗宽估计模型以及在其他文献中报道的方法 相比,具有较高的估计精度和鲁棒性．

基于自回归方法的Blazar天体3C 279和OJ 287光变周期研究

探索Blazar光变资料中的周期或准周期变化是1个有待深入研究的领域.由于光变资料的复杂性,目前寻找周期的算法还不够完善.文中以现代谱估计为基础,详细论述了自回归(Auto-regressive,AR)模型谱估计方法和最大熵谱估计的基本原理,分析了阶数选择对模型的重要影响,并把这些方法应用到类星体3C 279和BL Lac天体OJ287的光变周期分析中,得到它们的光变周期分别为7.14和11.76 yr.通过验证,自回归模型谱估计方法由于其分辨率高,可以作为1种较好的分析周期的方法.最后指出在应用谱估计分析Blazar天体的光变周期注意事项.

X射线荧光光谱分析法同时测定化探样品中多组分的含量

采用粉末压片制样法,利用PANalytical Axios型波长色散X荧光光谱仪同时对化探样品中的Fe2O3、Al2O3、Cr、Co、Ni、Cu、Zn、Pb等36种主、次和痕量组分进行测定。采用基本参数法,结合PH模式的经验系数法校正光谱干扰和集体效应。用国家标准物质做检验,测量结果与标样认定值吻合,用国家一级标准物质GBW 07401做精密度试验,统计结果RSD(n=10)除Br、Ce、Co、Ge、La、Mo、U、Sn、Sc和Nd小于10%,其余均小于5%。